Heart failure (HF) is responsible for more rehospitalizations than any other diagnosis in the United States. Frequent re-hospitalizations among patients with HF are a significant financial burden on patients, the families, and the public health system. HF frequently requires intensive daily monitoring and remote monitoring via telehealth technology in the home has emerged as a potential solution to manage HF patients in the community and prevent rehospitalization. However, in clinical trials the impact of THC on rehospitalization rates has been mixed. Little is known about the characteristics of patients most likely to respond positively to THC or of those who may need additional interventions. The proposed study will identify predictors of all-cause rehospitalization and heart failure-related rehospitalization during the home healthcare episode among HF patients receiving telehomecare. Using the OASIS-C dataset of approximately 1200 patients, this study will identify the patient characteristics that best predict response to THC and will lead us to implement the most appropriate interventions for the HF population. In the long term, improving how we target THC will optimize the use of this expensive technology to reduce the burden of rehospitalizations for patients, families and the healthcare system. Consistent with the National Institute of Nursing Research priorities, this work will improve the use of technology in healthcare.